Multimedia Information Retrieval Using Fuzzy Cluster-Based Model Learning

Date

2017-07-12

Author

Sattari, Saeid
Yazıcı, Adnan

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Multimedia data, particularly digital videos, which contain various modalities (visual, audio, and text) are complex and time consuming to model, process, and retrieve. Therefore, efficient methods are required for retrieval of such complex data. In this paper, we propose a multimodal query level fusion approach using a fuzzy cluster-based learning method to improve the retrieval performance of multimedia data. Experimental results on a real dataset demonstrate that employing fuzzy clustering achieves notable improvement in the concept-based query retrieval performance.

Subject Keywords

Correlation, Visualization, Multimedia communication, Videos, Correlation coefficient, Computational modeling, Semantics

URI

https://hdl.handle.net/11511/52897

Collections

Department of Computer Engineering, Conference / Seminar

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Citation Formats

S. Sattari and A. Yazıcı, “Multimedia Information Retrieval Using Fuzzy Cluster-Based Model Learning,” Naples, Italy, 2017, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/52897.